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Visar resultat 1 - 5 av 3053 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Nikolaos Staikos; [2024]
    Nyckelord :Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

    Sammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER

  2. 2. Metaller i Vombsjön - Mygglarver som bioindikator för miljöövervakning

    Kandidat-uppsats, Lunds universitet/Centrum för miljö- och klimatvetenskap (CEC)

    Författare :Siri Bengtsson; [2024]
    Nyckelord :Bioindicators; Chironomidae; Freshwater source; Lake Vomb; Metal concentrations; Pollution; Sediment sampling; Earth and Environmental Sciences;

    Sammanfattning : This study investigates concentrations of eight metals (Cu, Zn, Cd, Pb, Hg, Cr, Ni, As) in the freshwater resource Lake Vomb, located in the south of Sweden (Scania), and explores the potential use of deformed Chironomidae larvae as bioindicator. Sediment samples from six locations were analysed against threshold values from the Swedish Agency for Marine and Water Management and background values from the Swedish Environmental Protection Agency. LÄS MER

  3. 3. Multicriteria Evaluation in Real Estate Land-use Suitability Analysis: The case of Volos, Greece

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Panagiotis Dimitrios Tsachageas; [2024]
    Nyckelord :Geography; GIS; Real Estate; Multicriteria Evaluation; Fuzzy; AHP; Earth and Environmental Sciences;

    Sammanfattning : The integration of Geographic Information Systems (GIS) into real estate analysis has long been considered an interesting interdisciplinary pursuit, but has yet to become mainstream. Despite the increasing academic focus over the last twenty years, this endeavour has mostly been approached from the scientific side of Geography. LÄS MER

  4. 4. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Anastasia Sarelli; [2024]
    Nyckelord :Geography; GIS; Land Cover Classification; Landsat; Machine Learning; Earth and Environmental Sciences;

    Sammanfattning : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. LÄS MER

  5. 5. Integrating Local Knowledge into the Spatial Analysis of Wind Power: The case study of Northern Tzoumerka, Greece

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Athanasios Senteles; [2024]
    Nyckelord :Geography; Geographical Information Systems; MCDA; wind energy; local knowledge; Greece; Earth and Environmental Sciences;

    Sammanfattning : Increasing demand for incorporating renewable energy projects into the national energy mix, is associated with international and European efforts to tackle the negative effects of climate change and strengthen energy resilience. Greece, as a member country of the European Union, has acknowledged that necessity, by implementing a national program aiming to significantly reduce Green House Gas Emissions and upscale Renewable Energy Sources (RES) project development in upcoming years. LÄS MER